By MICHAEL FITZGERALD
THAT hoariest of real estate truisms - location, location, location - may
soon be a clarion call for all sorts of businesses.
We're in the midst of a boom in devices that show where people are at any
point in time. Global positioning systems are among the hottest consumer
electronics devices ever, says Clint Wheelock, chief research officer at ABI
Research, a technology market follower. And cellphones increasingly come
with G.P.S. chips. All of these devices churn out data that says something
about how people live.
Such data could redefine what we know about consumer behavior, giving
businesses early insight into economic trends, better ways to determine
sites for offices and retail stores, and more effective ways to advertise.
Just this month, the journal Nature published a paper that looked at
cellphone data from 100,000 people in an unnamed European country over six
months and found that most follow very predictable routines. Knowing those
routines means that you can set probabilities for them, and track how they
"What we do is really not random, even though it may appear random," says
Albert-László Barabási, a physicist at Northeastern University who is one of
the paper's authors.
It's hard to make sense of such data, but Sense Networks, a software
analytics company in New York, earlier this month released Macrosense, a
tool that aims to do just that. Macrosense applies complex statistical
algorithms to sift through the growing heaps of data about location and to
make predictions or recommendations on various questions - where a company
should put its next store, for example. Gregory Skibiski, 34, the chief
executive and a co-founder of Sense, says the company has been testing its
software with a major retailer, a major financial services firm and a large
Tony Jebara, also 34, the chief scientist and another co-founder of Sense,
said, "We can predict tourism, we can tell you how confident consumers are,
we can tell retailers about, say, their competitors, who's coming in from
Mr. Jebara, who is also an associate professor of computer science at
Columbia University, says the key to drawing such conclusions starts with
having very large sets of data that go back several years. Sense's models
were developed initially from sources like taxicab companies that let it
look at location data over such a period. Sense also uses publicly available
data, like weather information, and other nonpublic sources that it would
not disclose. "We had three-quarters of a billion data points from just one
city," Mr. Skibiski says.
Mr. Jebara's statistical models interpret those patterns and look at whether
they correlate with things in the real world, like tourism levels or retail
sales. The algorithms are complex. Even so, the model doesn't work for
everything Sense tries it on, often because more data is needed. But Mr.
Jebara says that when it has the data, the model works well. Several hedge
funds made an investment in Sense earlier this year.
The Macrosense tool lets companies engage in "reality mining," a phrase
coined by Sandy Pentland, an M.I.T. researcher who was also a co-founder of
Sense and now advises it on privacy issues.
Sense is not the only company engaged in reality mining. Inrix, a Microsoft
spin-off, uses traffic data to predict traffic patterns. Path Intelligence
of Britain monitors traffic flow in shopping centers by tracking cellphones.
Reality mining raises instant questions about privacy, especially when
cellphone data is involved. In the United States, it is illegal in many
cases for cellphone companies to share customers' location data without
Mr. Skibiski says that Sense is interested only in aggregate data and that
it's looking for broad patterns, not the specific behavior of individuals.
But he recognizes the privacy issue. He says he believes that people should
own their own data, control when it is disclosed and receive some
remuneration for it. His original idea in 2002 was to pay people for their
data, but a formula for doing so proved too complicated.
Instead, Sense decided to trade services for data. On the same day it
released Macrosense, it announced a new software package called Citysense,
which uses location data to show where people are going, say, for nightlife,
and maps their activity. Consumers who have iPhones or BlackBerrys can sign
up for the service, which does not ask for personal information. Over time,
the software will learn their patterns and recommend places they might like
to go, or show them where other people with similar patterns are going. If
they want to purge their data, they can do so at any time.
There's little doubt that products we use everyday, like our cellphones or
cars, will increasingly allow for us to be tracked. And after years of hype,
there also seems to be demand for services built around location. Gartner, a
technology researcher and consulting firm, says that the market - which
includes various navigation and search devices and subscriptions and
services - will nearly triple in revenue this year, to $1.3 billion from
$485 million in 2007, and will reach $8 billion in 2011.
Annette Zimmermann, a Gartner analyst, says Macrosense seems to have a novel
offering, one with a potentially large market.
"So many companies are just sitting on data" that they can't do much with,
she says. That could make Macrosense a powerful tool.
Still, Sense's model is not a sure thing.
"The reality is that location data is new, and we don't have 10 years of
history to work from," says Ted Morgan, the chief executive and founder of
Skyhook Wireless, which sells a service that lets people use WiFi network
access points to get information about their location.
"But if their algorithms can do the things they say, we'd probably do a lot
with them," Mr. Morgan says.
Michael Fitzgerald writes about business, technology and culture. E-mail:
June 22, 2008
Copyright 2008 The New York Times Company
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